| Literature DB >> 32344461 |
Hui Li1, Min Wang2, Weijun Li1, Linlin He1, Yuanyuan Zhou1, Jiantang Zhu1, Ronghui Che1, Marilyn L Warburton3, Xiaohong Yang2, Jianbing Yan4.
Abstract
Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance-heterogeneity genome-wide association study to examine the contribution of variance heterogeneity to oil-related quantitative traits. We identified 79 unique variance-controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance-heterogeneity genes for 21 oil-related traits using the Levene test (P < 1.0 × 10-5 ). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean-effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two-hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high-oil maize (Zea mays L.).Entities:
Keywords: gene × gene interactions; maize; mean-effect SNP; vGWAS; variance heterogeneity
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Year: 2020 PMID: 32344461 DOI: 10.1111/tpj.14786
Source DB: PubMed Journal: Plant J ISSN: 0960-7412 Impact factor: 6.417